Competitive throughput in multi-hop wireless networks despite adaptive jamming

Richa, Andr{ '{e}}a W.; Scheideler, Christian; Schmid, Stefan; Zhang, Jin

doi:10.1007/s00446-012-0180-x

Cited by 28 publications

(10 citation statements)

References 44 publications

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“…Many models have been proposed to depict jamming in wireless networks, including the oblivious jamming mode [30][31][32][33][34][35][36] , in which jamming is initially fixed and unrelated to the particular algorithm execution; the adaptive adversary jamming mode [29,37,38] , in which the adversary can make use of all the history information in a network to online decide the jamming situation in each time step; and the reactive adversary jamming pattern [27,28,39,40] , in which the adversary can not only know the historical information but also use the current network information to make a jamming decision. However, in all of the models mentioned above, jamming is regarded as a uniform binary phenomenon, i.e., all nodes in the network have the same ambient noise, and once the network is jammed, all transmissions in the network fail.…”

Section: Related Workmentioning

confidence: 99%

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Implementation of abstract MAC layer under jamming

Zou

Chen

et al. 2022

Tsinghua Sci. Technol.

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In the past decades, with the widespread implementation of wireless networks, such as the Internet of Things, an enormous demand for designing relative algorithms for various realistic scenarios has arisen. However, with the widening of scales and deepening of network layers, it has become increasingly challenging to design such algorithms when the issues of message dissemination at high levels and the contention management at the physical layer are considered. Accordingly, the abstract medium access control (absMAC) layer, which was proposed in 2009, is designed to solve this problem. Specifically, the absMAC layer consists of two basic operations for network agents: the acknowledgement operation to broadcast messages to all neighbors and the progress operation to receive messages from neighbors. The absMAC layer divides the wireless algorithm design into two independent and manageable components, i.e., to implement the absMAC layer over a physical network and to solve higher-level problems based on the acknowledgement and progress operations provided by the absMAC layer, which makes the algorithm design easier and simpler. In this study, we consider the implementation of the absMAC layer under jamming. An efficient algorithm is proposed to implement the absMAC layer, attached with rigorous theoretical analyses and extensive simulation results. Based on the implemented absMAC layer, many high-level algorithms in non-jamming cases can be executed in a jamming network.

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Section: Related Workmentioning

confidence: 99%

“…Many jamming models have already been proposed [27][28][29] in the past years, which are based on graph-based and physical interference models. However, all of them regard jamming as a binary phenomenon, which means that when agents are jammed by relatively large ambient noise, they receive nothing.…”

Section: Introductionmentioning

confidence: 99%

Implementation of abstract MAC layer under jamming

Zou

Chen

et al. 2022

Tsinghua Sci. Technol.

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“…Our work does not focus on stability, as we assume errors controlled by an unbounded adversary that can always prevent it. The work in [12] considers the problem of devising local access control protocols for wireless networks with a single channel, that are provably robust against adaptive adversarial jamming. At certain time steps, the adversary can jam the communication in the channel in such a way that the wireless nodes do not receive messages (unlike our work, where the receiver might receive a message, but it might contain bit errors).…”

Section: Related Workmentioning

confidence: 99%

“…This throughput metric makes sense for a link without errors or with random errors, where the full capacity of the link can be achieved under certain conditions. However, if adversarial bit errors can occur during the transmission of packets, the full capacity is usually not achievable by any protocol, unless restrictions are imposed on the adversary [2,12]. Moreover, since a bit error renders a whole packet unusable (unless costly techniques like PPR [4] are used), a throughput equal to the capacity minus the bits with errors is not achievable either.…”

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confidence: 99%

Measuring the impact of adversarial errors on packet scheduling strategies

Anta

Georgiou

Kowalski

et al. 2015

J Sched

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In this paper we explore the problem of achieving efficient packet transmission over unreliable links with worst case occurrence of errors. In such a setup, even an omniscient offline scheduling strategy cannot achieve stability of the packet queue, nor is it able to use up all the available bandwidth. Hence, an important first step is to identify an appropriate metric for measuring the efficiency of scheduling strategies in such a setting. To this end, we propose a relative throughput metric which corresponds to the long term competitive ratio of the algorithm with respect to the optimal. We then explore the impact of the error detection mechanism and feedback delay on our measure. We compare instantaneous error feedback with deferred error feedback, that requires a faulty packet to be fully received in order to detect the error. We propose algorithms for worst-case adversarial and stochastic packet arrival models, and formally analyze their performance. The relative throughput achieved by these algorithms is shown to be close to optimal by deriving lower bounds on the relative throughput of the algorithms and almost matching upper bounds for any algorithm in the considered settings. Our collection of results demonstrate the potential of using instantaneous feedback to improve the performance of communication systems in adverse environments.

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“…In a surprising breakthrough, Awerbuch et al [2] showed that good throughput is possible with a small number of access attempts, even if jamming causes disruption for a constant fraction of the execution. A number of elegant results have followed [37,44,[49][50][51][52][53], with good guarantees on throughput and access attempts.…”

Section: Introductionmentioning

confidence: 99%

How to Scale Exponential Backoff: Constant Throughput, Polylog Access Attempts, and Robustness

Bender¹,

Fineman²,

Gilbert³

et al. 2015

Proceedings of the Twenty-Seventh Annual ACM-SIAM Symposium on Discrete Algorithms

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Randomized exponential backoff is a widely deployed technique for coordinating access to a shared resource. A good backoff protocol should, arguably, satisfy three natural properties: (i) it should provide constant throughput, wasting as little time as possible; (ii) it should require few failed access attempts, minimizing the amount of wasted effort; and (iii) it should be robust, continuing to work efficiently even if some of the access attempts fail for spurious reasons. Unfortunately, exponential backoff has some well-known limitations in two of these areas: it provides poor (sub-constant) throughput (in the worst case), and is not robust (to adversarial disruption).The goal of this paper is to "fix" exponential backoff by making it scalable, particularly focusing on the case where processes arrive in an on-line, worst-case fashion. We present a relatively simple backoff protocol, Re-Backoff, that has, at its heart, a version of exponential backoff. It guarantees expected constant throughput with dynamic process arrivals and requires only an expected polylogarithmic number of access attempts per process.Re-Backoff is also robust to periods where the shared resource is unavailable for a period of time. If it is unavailable for D time slots, Re-Backoff provides the following guarantees. When the number of packets is a finite n, the average expected number of access attempts for successfully sending a packet is O(log 2 (n + D)). In the infinite case, the average expected number of access attempts for successfully sending a packet is O(log 2 (η + D)) where η is the maximum number of processes that are ever in the system concurrently.

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Competitive throughput in multi-hop wireless networks despite adaptive jamming

Cited by 28 publications

References 44 publications

Implementation of abstract MAC layer under jamming

Implementation of abstract MAC layer under jamming

Measuring the impact of adversarial errors on packet scheduling strategies

How to Scale Exponential Backoff: Constant Throughput, Polylog Access Attempts, and Robustness

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